Going from an organization without AI, to one with it, is a big step. While you want to leverage the benefits that come with this technology, you need to have a strong change management strategy ready to go. If you fail to cover this much-needed step, you may end up with a failed adoption that ends up costing the company big-time.

Explain the Benefits

One of the most important aspects to cover in a change management strategy is answering the “What’s in it for me” question. When you have a strong understanding of how AI solutions help end users at all levels of the company, you can easily convey the benefits that come with using a new solution.

Avoid going through the feature list when you try to help end users understand why you’re making the change. While that explains what the platform does, it doesn’t get into how it actually helps on with their job duties.

Take the time to tailor the benefits list to their technical understanding. You want to relate this information to their current workflows. If the AI solution cuts down the time it takes to do a certain task or improves their experience when going through a workflow, then explain exactly how it will work in practice.

Provide Ample Training

Some organizations fall into the trap of spending most of their budget on the new AI solution, and not nearly enough on training. They set themselves up for failure right out of the gate, and it’s hard to recover from a lack of end-user adoption in this situation.

Don’t skimp on the training materials. Make sure that you have multiple formats that are easily accessible from multiple devices. If you can get a solution that comes with expert trainer sessions, you can get started off right.

Pay close attention to the training resources that people actually end up using. You may have departments that prefer in-person group training sessions, while others want to read through a guide when they’re on their tablets at home.

Empower end users with more materials in their preferred formats, and address any educational gaps that may exist. Going all out on your training materials does increase your investment in AI, but it helps you minimize the chance that people fail to start using the new platform.

Make Yourself Available to End Users

No matter how much you put into training material, you won’t always be able to cover every single question end users may have. An easy to use communication channel that gets prompt answers is a must during the AI rollout.

Make it clear who the end users should contact, how long it will take to get a response and any escalation path that’s available. By promoting transparency in this area of the deployment, you encourage users to come to you when they encounter problems. Their feedback is incredibly valuable, especially if this is the first time you have handled a large-scale shift in your company’s infrastructure.

Roll Out New Solutions Slowly

AI platforms aren’t an all or nothing endeavor. There’s no rule that says you need to try to deploy a new AI solution to your entire organization at once. In fact, that’s a horrible way of going about things. Pick your testing environments, ideally filled with people who are more tech-savvy than the typical user. They can provide valuable feedback about potential roadblocks, discover whether the platform functions properly in the production environment, and determine whether the application actually works as well as expected for their purposes.

Another benefit of a slow rollout is building up your advocates within the organization. If the entire accounting department is raving about the new time-saving AI solution, then the rest of the company is going to get excited about the new development. They go into the platform with a positive attitude, even if they’re not quite sure what to expect.

AI has the power to transform your organization, but you won’t get strong adoption numbers if you don’t have a change management strategy in place. Cover all of your bases before you begin this process. It’s well worth the time that you sink into it.

Big data, the Internet of Things and highly integrated platforms make it possible to get more advertising data than ever before. However, more data doesn’t necessarily mean more value. If you don’t have a way to analyze the data points and create actionable insights, then all it is is another table in the database.

Artificial Intelligence is capable of working its way through massive data sets from disparate sources, and figuring out how you can get the most out of your advertising spend. It looks at historical trends, first and third-party data sources, lookalike audiences and more to help your company optimize advertising campaigns.

Programmatic Advertising

The place where AI really shines in advertising is programmatic. You get the opportunity to leverage all of the data you have available, as well as that of the advertising platform, to make real-time changes, so every ad goes to the best possible user in that moment.

Trying to manage this type of campaign is literally impossible for a human, due to the complex calculations that occur almost instantaneously. AI, on the other hand, not only does an amazing job at this, it gets better over time. It uses machine learning to evaluate every ad view, click and conversion, so it amasses even more information than you already had. Optimizing performance just got a lot easier with this solution available.